Bayesian Statistical Analysis using Python - Part 1 | SciPy 2014 | Chris Fonnesbeck

[Fordance]

At 50:06, the way equation was written is not usual. One way to write it is: P(w=1| s1=0, s2=0) = P(s1=0, s2=0|w=1)*P(w=1) / (P(s1=0, s2=0|w=1)*P(w=1) + P(s1=0, s2=0|w=0)*P(w=0) ). The calculation is correct.

[jonathannavarrete]

A little theory goes a long way. Finally (introductory) Bayesian theory for the layperson from a real statistician.

[AlfradNobel]

i cant read the notebook. How can i read codes for coal data mining problem ?

[acampoverdeify]

The negative Bernoulli distribution is wrong @56:15, it should be a binomial coefficient, not a ratio.

[littlerainyone]

I was drawn to these videos because I wanted to see what PyMC is doing under the hood, for example, with respect to Gibbs sampling. I was following the presentation just fine until I got to the big messy conditional probability expression for tau, at which point I hit a brick wall. Chris Fonnesbeck indicates you "need to do a little mathematical wrangling" to derive this categorical distribution. Where should I look to find out how the "wrangling" is done? I haven't read Gelman, but I own it, and it is mentioned several times in this conference lecture. Any tips on what I ought to read to understand the details of Gibbs sampling (preferably not entire books) would be much appreciated.

[vvd]

I couldn't find the link to material on github. Could somebody post the link ?